Effects of Soil Parameter Variabilities on the Estimation of Ground‐Motion Amplification Factors
Why this work is in the frame
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Bibliographic record
Abstract
Ground‐motion amplification factors (GMAFs) are used to characterize amplification of a ground motion propagating from the bedrock to the ground surface. They are usually determined by ground response analysis, in which the soil parameter variabilities and input motion uncertainties contribute to their uncertainty. The construction of design response spectra requires mean GMAFs or GMAFs with different probability levels. Thus, it is significant to study the sensitivity of soil parameter variabilities and the number of random soil profiles for the estimation of GMAFs. This study investigates the minimum number of random soil profiles required to represent the extent of the epistemic uncertainty in the GMAFs obtained from ground response analysis. It shows that at least 20 and 60 random soil profiles are respectively required to estimate the mean and standard deviations of GMAFs with the maximum relative difference below 10%. In addition, potential reasons for a reduction in the mean GMAFs resulting from randomization of the soil column properties are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it